The moisture content of persimmons during drying was monitored by hyperspectral imaging technology. All persimmons were dried using a hot-air dryer at 40 °C and divided into seven groups according to drying time: semi-dried persimmons (Cont), 1 day (DP-1), 2 days (DP-2), 3 days (DP-3), 4 days (DP-4), 5 days (DP-5), and 6 days (DP-6). Shortwave infrared hyperspectral spectra and moisture content of all persimmons were analyzed to develop a prediction model using partial least squares regression. There were obvious absorption bands: two at approximately 971 nm and 1452 nm were due to water absorption related to O-H stretching of the second and first overtones, respectively. The R-squared value of the optimal calibration model was 0.9673, and the accuracy of the moisture content measurement was 95%. These results indicate that hyperspectral imaging technology can be used to predict and monitor the moisture content of dried persimmons during drying.
Keywords: Dried persimmons; Hyperspectral imaging; Moisture content; Partial least squares regression; Spectra pre-processing.
© The Korean Society of Food Science and Technology 2020.